Fig. 2: Performance comparison of process-based (E-HYPE) and hybrid models (E-HYPE integrated with GLM, QM, RF and LSTM) in predicting streamflow total volume (SMAE), high extremes (NSE) and low extremes (logNSE).
From: Hybrid approaches enhance hydrological model usability for local streamflow prediction
The cumulative distribution of model performance is shown using the SMAE (a), NSE (b), and logNSE (c) metrics (see Methods). Perfect performance corresponds to 0 for SMAE and 1 for NSE and logNSE. The grey line represents E-HYPE, while colored lines with varying styles denote hybrid models with different post-processing methods. Performance improves as the lines approach the perfect value marker on the x-axis. The x-axis represents the metric values, and the y-axis indicates the proportion of stations with performance not exceeding the corresponding metric level. The inset plot provides a zoomed-in view of the most common range (highlighted on the x-axis) for clarity.
